The Optical Bioimaigng Laboratory have been developing novel optical imaging and spectroscopy methods for biomedical applications. An in-vivo fluorescence imaging method, focal modulation microscopy, has been invented and licensed to a global leader in microscopy. High performance diffuse optical tomography has been actively developed for optical mammography and brain imaging. We are also interested in designing and fabrication of nanostructures as new optical imaging contrast agent, especially for molecular imaging with optical coherence tomography.
Bioimaging offers synergies and exciting new possibilities for collaboration with existing research thrusts in the Department, including those in biosensors and signal processing, nanobioengineering, biomechanics, biomaterials and tissue engineering. Through the interfacing element of light, we aim to have deeper understanding of fundamental science behind biological organism and process; we also seek to innovate and develop new instrumentation for imaging and diagnostic applications in clinical research.

Our work can be summarized into three major areas:

1.  Microscopy

2. Tomography

3. Spectroscopy


Deep Imaging With Focal Modulation Microscopy
Raman Spectroscopy and Imaging

 

 


Functional Computational Anatomy Lab

Computational Functional Anatomy (CFA) is the mathematical study of anatomical configurations and signals associated with anatomy and functions in anatomical coordinates using multi-modal images. Its ultimate goal is to identify image biomarkers associated with a specific disease.

Currently, most of our work focuses on the development of medical image analysis tools to assess anatomical shape and functions of the human brain in magnetic resonance imaging (MRI), including structural MRI, functional MRI, and diffusion tensor imaging (DTI). Special tools developed are listed:

 
1. Brain Mapping

        >>  Large Deformation Diffeomorphic Metric Mapping (LDDMM) tools register images, landmark points, curves, and surface meshes.
        >> Parallel Transport in Diffeomorphisms tool tracks longitudinal changes of anatomy.

2. Shape Analysis Pipeline

        >>The pipeline has several key components, structural delineation, segmentation denoising, surface momentum maps recording shape variation between anatomies
             as well as random field statistical analysis for detecting group differences in anatomical shape. This pipeline fully automatically processes raw MRI scans and              allows us to assess 3. large scale MRI database.

3.  Random Field Analysis

4. Spatial Smoothing Functional Signals on the Cortex

5. Surface-based fMRI Analysis.

 
Figure shows schematic of the multi-structure shape analysis pipeline.